Instructions to use AdarshRL/gemma2-9b-terraform-architect-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AdarshRL/gemma2-9b-terraform-architect-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/tmp/base_model_dir/gemma-2-9b") model = PeftModel.from_pretrained(base_model, "AdarshRL/gemma2-9b-terraform-architect-adapter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 487413e0b19f33da3bb5dcd61bc0d5cd50a4bb5e0d4e848c4e69cfd09f6d4bb8
- Size of remote file:
- 34.4 MB
- SHA256:
- 0bfe44359210dc8f84af19015ad17cf8b6723497249313f245b98596a8f1d7a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.